Literature DB >> 32506550

Experimental assessment of microwave ablation computational modeling with MR thermometry.

Pegah Faridi1, Paul Keselman2, Hojjatollah Fallahi1, Punit Prakash1.   

Abstract

PURPOSE: Computational models are widely used during the design and characterization of microwave ablation (MWA) devices, and have been proposed for pretreatment planning. Our objective was to assess three-dimensional (3D) transient temperature and ablation profiles predicted by MWA computational models with temperature profiles measured experimentally using magnetic resonance (MR) thermometry in ex vivo bovine liver.
MATERIALS AND METHODS: We performed MWA in ex vivo tissue under MR guidance using a custom, 2.45 GHz water-cooled applicator. MR thermometry data were acquired for 2 min prior to heating, during 5-10 min microwave exposures, and for 3 min following heating. Fiber-optic temperature sensors were used to validate the accuracy of MR temperature measurements. A total of 13 ablation experiments were conducted using 30-50 W applied power at the applicator input. MWA computational models were implemented using the finite element method, and incorporated temperature-dependent changes in tissue physical properties. Model-predicted ablation zone extents were compared against MRI-derived Arrhenius thermal damage maps using the Dice similarity coefficient (DSC).
RESULTS: Prior to heating, the observed standard deviation of MR temperature data was in the range of 0.3-0.7°C. Mean absolute error between MR temperature measurements and fiber-optic temperature probes during heating was in the range of 0.5-2.8°C. The mean DSC between model-predicted ablation zones and MRI-derived Arrhenius thermal damage maps for 13 experimental set-ups was 0.95. When comparing simulated and experimentally (i.e. using MRI) measured temperatures, the mean absolute error (MAE %) relative to maximum temperature change was in the range 5%-8.5%.
CONCLUSION: We developed a system for characterizing 3D transient temperature and ablation profiles with MR thermometry during MWA in ex vivo liver tissue, and applied the system for experimental validation of MWA computational models.
© 2020 American Association of Physicists in Medicine.

Entities:  

Keywords:  MR thermometry; MRI-guided interventions; computational modeling; microwave ablation; model validation

Mesh:

Year:  2020        PMID: 32506550      PMCID: PMC7719571          DOI: 10.1002/mp.14318

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  42 in total

1.  Experimental measurement of microwave ablation heating pattern and comparison to computer simulations.

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2.  Magnetic resonance temperature imaging validation of a bioheat transfer model for laser-induced thermal therapy.

Authors:  D Fuentes; C Walker; A Elliott; A Shetty; J D Hazle; R J Stafford
Journal:  Int J Hyperthermia       Date:  2011       Impact factor: 3.914

3.  Quantification of tissue shrinkage and dehydration caused by microwave ablation: experimental study in kidneys for the estimation of effective coagulation volume.

Authors:  Christof M Sommer; Steffen A Sommer; Theresa Mokry; Theresa Gockner; Daniel Gnutzmann; Nadine Bellemann; Anne Schmitz; Boris A Radeleff; Hans U Kauczor; Ulrike Stampfl; Philippe L Pereira
Journal:  J Vasc Interv Radiol       Date:  2013-06-20       Impact factor: 3.464

4.  Ex vivo tissue-type independence in proton-resonance frequency shift MR thermometry.

Authors:  R D Peters; R S Hinks; R M Henkelman
Journal:  Magn Reson Med       Date:  1998-09       Impact factor: 4.668

5.  Influence of the target tissue size on the shape of ex vivo microwave ablation zones.

Authors:  Marta Cavagnaro; Claudio Amabile; Simone Cassarino; Nevio Tosoratti; Rosanna Pinto; Vanni Lopresto
Journal:  Int J Hyperthermia       Date:  2015-02-13       Impact factor: 3.914

6.  In vitro artefact assessment of a new MR-compatible microwave antenna and a standard MR-compatible radiofrequency ablation electrode for tumour ablation.

Authors:  Rüdiger Hoffmann; Hansjörg Rempp; Frank Eibofner; David-Emanuel Keßler; Gunnar Blumenstock; Jakob Weiß; Philippe L Pereira; Konstantin Nikolaou; Stephan Clasen
Journal:  Eur Radiol       Date:  2015-07-02       Impact factor: 5.315

7.  Numerical models to evaluate the temperature increase induced by ex vivo microwave thermal ablation.

Authors:  M Cavagnaro; R Pinto; V Lopresto
Journal:  Phys Med Biol       Date:  2015-03-31       Impact factor: 3.609

8.  Dual-echo Z-shimmed proton resonance frequency-shift magnetic resonance thermometry near metallic ablation probes: Technique and temperature precision.

Authors:  Yuxin Zhang; Megan E Poorman; William A Grissom
Journal:  Magn Reson Med       Date:  2017-02-10       Impact factor: 4.668

Review 9.  Computational modelling of microwave tumour ablations.

Authors:  Jason Chiang; Peng Wang; Christopher L Brace
Journal:  Int J Hyperthermia       Date:  2013-06       Impact factor: 3.914

Review 10.  Magnetic resonance-guided laser induced thermal therapy for glioblastoma multiforme: a review.

Authors:  Sarah E Norred; Jacqueline Anne Johnson
Journal:  Biomed Res Int       Date:  2014-01-16       Impact factor: 3.411

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  3 in total

1.  Microwave ablation of lung tumors: A probabilistic approach for simulation-based treatment planning.

Authors:  Jan Sebek; Pinyo Taeprasartsit; Henky Wibowo; Warren L Beard; Radoslav Bortel; Punit Prakash
Journal:  Med Phys       Date:  2021-05-27       Impact factor: 4.506

2.  Fat Quantification Imaging and Biophysical Modeling for Patient-Specific Forecasting of Microwave Ablation Therapy.

Authors:  Frankangel Servin; Jarrod A Collins; Jon S Heiselman; Katherine C Frederick-Dyer; Virginia B Planz; Sunil K Geevarghese; Daniel B Brown; Michael I Miga
Journal:  Front Physiol       Date:  2022-02-03       Impact factor: 4.566

3.  How large is the periablational zone after radiofrequency and microwave ablation? Computer-based comparative study of two currently used clinical devices.

Authors:  Macarena Trujillo; Punit Prakash; Pegah Faridi; Aleksandar Radosevic; Sergio Curto; Fernando Burdio; Enrique Berjano
Journal:  Int J Hyperthermia       Date:  2020       Impact factor: 3.914

  3 in total

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